Jupyter Notebook vs. Qlik AutoML

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Jupyter Notebook
Score 9.4 out of 10
N/A
Jupyter Notebook is an open-source web application that allows users to create and share documents containing live code, equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation, statistical modeling, data visualization, and machine learning. It supports over 40 programming languages, and notebooks can be shared with others using email, Dropbox, GitHub and the Jupyter Notebook Viewer. It is used with JupyterLab, a web-based IDE for…N/A
Qlik AutoML
Score 0.0 out of 10
N/A
Qlik AutoML is presented as an automated, no-code machine learning solution that enables users to create ML experiments, identify key drivers in data and train models. And make future predictions with full explainability data, and quickly publish the data or directly integrate models into Qlik Sense® apps for fully interactive analysis and what-if scenario planning.N/A
Pricing
Jupyter NotebookQlik AutoML
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Jupyter NotebookQlik AutoML
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Jupyter NotebookQlik AutoML
Considered Both Products
Jupyter Notebook
Chose Jupyter Notebook
As a beginner I tried all of them but finally due to simple and user friendly interface I opted it. I also tried visual basic which is also good platform with versatility, however for basic need it is the best.
Chose Jupyter Notebook
Jupyter is very easy to understand and easy to use. And can also be used by a student, freelancer, small industries, big industries. Jupyter also provides you a tool to work with machine learning and artificial intelligence.
Chose Jupyter Notebook
Negligible or no cost, Highly efficient, effective, scalable , hasslefree
Chose Jupyter Notebook
Jupyter Notebook is very attractive platform for new developers to code and to learn programming and perform tasks as compared to other IDE. It has very well and easy visualization, interactive programming and sharing the live code and slideshow is very easy as compare to …
Chose Jupyter Notebook
Jupyter is still the most well known and widely used platform I've seen. Using it over other competition like Zeppelin simply because of its availability, and my familiarity with its functionality.
Chose Jupyter Notebook
Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot …
Chose Jupyter Notebook
Well, so far Jupyter Notebook has been the better tool for me. It gives us more freedom & has more ability to train ML models & do the data visualization more efficiently. It's easier to operate & has a very simple-to-understand UI & with the support for taking data from …
Chose Jupyter Notebook
I have used PyCharm as well as Jupyter Notebook and for me, Jupyter wins almost every time. I really like its user-friend interface for someone who is new to python programming. The ability to run a big chunk of code part by part is a big game-changer for me. One thing I would …
Chose Jupyter Notebook
It should have cleaner support for multi-environment setup and should also increase the amount of features. Moreover, more support should be present for other programming languages. It should also have the option to set a specific location that opens up whenever I run command …
Chose Jupyter Notebook
Jupyter is easier to handle and user friendly.

We have free access to it and its cell by cell executing feature is amazing.
Chose Jupyter Notebook
Jupyter Notebook has a nicer interface than RStudio in our opinion and since most of our group is familiar with Jupyter Notebook it has made it a default choice. Overall the interactive programming as well as the easy visualizations, model deployment, and markdown made Jupyter …
Chose Jupyter Notebook
Jupyter Notebook is the core feature extended on by many commercial alternatives. The commercial alternatives have more feature integration with the rest of their portfolio. RStudio is another competitor for interactive and literate programming.

Chose Jupyter Notebook
haven't actually explored as I decided to use it on a friend 's recommendation.
Chose Jupyter Notebook
An interesting thing is that Jupyter Notebook is run on browser environments which may or may not be a positive feature according to cases. VS Code on [the] other hand doesn't use any interface and can run Jupyter Notebooks too. Sometimes my browser consumes too much RAM due to …
Chose Jupyter Notebook
With Jupyter Notebook besides doing data analysis and performing complex visualizations you can also write machine learning algorithms with a long list of libraries that it supports. You can make better predictions, observations etc. with it which can help you achieve better …
Chose Jupyter Notebook
I like Jupyter Notebook over the other two because it keeps my work more organized. It helps me to structure my workflow and the ability to run commands in chunks keeps me from being confused when coming back to the work after some time.
Chose Jupyter Notebook
I selected Jupyter Notebook because this is better integrated with the existing production systems than optional tools (for example, R). It is also commonly used tool within the scientist community.
Chose Jupyter Notebook
When I tried Zeppelin in 2017, it was still in initial versions, Jupyter was way ahead as of then. Zeppelin had limitations and I wasn't confident of it making progress as much as Jupyter.
Qlik AutoML

No answer on this topic

Features
Jupyter NotebookQlik AutoML
Platform Connectivity
Comparison of Platform Connectivity features of Product A and Product B
Jupyter Notebook
9.0
Ratings
7% above category average
Qlik AutoML
-
Ratings
Connect to Multiple Data Sources10.00 Ratings00 Ratings
Extend Existing Data Sources10.00 Ratings00 Ratings
Automatic Data Format Detection8.50 Ratings00 Ratings
MDM Integration7.40 Ratings00 Ratings
Data Exploration
Comparison of Data Exploration features of Product A and Product B
Jupyter Notebook
7.0
Ratings
18% below category average
Qlik AutoML
-
Ratings
Visualization6.00 Ratings00 Ratings
Interactive Data Analysis8.00 Ratings00 Ratings
Data Preparation
Comparison of Data Preparation features of Product A and Product B
Jupyter Notebook
9.5
Ratings
15% above category average
Qlik AutoML
-
Ratings
Interactive Data Cleaning and Enrichment10.00 Ratings00 Ratings
Data Transformations10.00 Ratings00 Ratings
Data Encryption8.50 Ratings00 Ratings
Built-in Processors9.30 Ratings00 Ratings
Platform Data Modeling
Comparison of Platform Data Modeling features of Product A and Product B
Jupyter Notebook
9.3
Ratings
10% above category average
Qlik AutoML
-
Ratings
Multiple Model Development Languages and Tools10.00 Ratings00 Ratings
Automated Machine Learning9.20 Ratings00 Ratings
Single platform for multiple model development10.00 Ratings00 Ratings
Self-Service Model Delivery8.00 Ratings00 Ratings
Model Deployment
Comparison of Model Deployment features of Product A and Product B
Jupyter Notebook
10.0
Ratings
16% above category average
Qlik AutoML
-
Ratings
Flexible Model Publishing Options10.00 Ratings00 Ratings
Security, Governance, and Cost Controls10.00 Ratings00 Ratings
Best Alternatives
Jupyter NotebookQlik AutoML
Small Businesses
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Score 10.0 out of 10
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Score 7.7 out of 10
Medium-sized Companies
Posit
Posit
Score 10.0 out of 10
Posit
Posit
Score 10.0 out of 10
Enterprises
Posit
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Score 10.0 out of 10
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All AlternativesView all alternativesView all alternatives
User Ratings
Jupyter NotebookQlik AutoML
Likelihood to Recommend
10.0
(0 ratings)
-
(0 ratings)
Usability
10.0
(0 ratings)
-
(0 ratings)
Support Rating
9.0
(0 ratings)
-
(0 ratings)
User Testimonials
Jupyter NotebookQlik AutoML
Likelihood to Recommend
I would rate it 9/10 while recommending Jupyter Notebook as it offers me a wide range of functionality to operate. It is very well suited for someone who is new to python programming as the user interface helps you build code line by line. I personally have written multiple programs in Python using Jupyter Notebook as it helps me organize long code by breaking it in a structure. Also the ability to write comments using '#' helps a lot to a reader understand the code.
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Pros
  • Coding and error correction line by line
  • Simple and Effectiveness
  • Easy to use for visualisation and presentation of code
  • Could be used at any place any time without hassle
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Cons
  • Need more Hotkeys for creating a beautiful notebook. Sometimes we need to download other plugins which messes [with] its default settings.
  • Not as powerful as IDE, which sometimes makes [the] job difficult and allows duplicate code as it get confusing when the number of lines increases. Need a feature where [an] error comes if duplicate code is found or [if a] developer tries the same function name.
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Usability
Jupyter is highly simplistic. It took me about 5 mins to install and create my first "hello world" without having to look for help. The UI has minimalist options and is quite intuitive for anyone to become a pro in no time. The lightweight nature makes it even more likeable.
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Support Rating
I haven't had a need to contact support. However, all required help is out there in public forums.
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Alternatives Considered
Jupyter Notebook is unique in that it offers a flexible, lightweight, easy-to-replicate way of organizing your code in a visually intuitive fashion that can be exported in a number of formats. I've found that the broad functionalities available within the notebooks suit a lot of needs I have for EDA, modeling, and data export that makes other software products fairly redundant.
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No answers on this topic
Return on Investment
  • Positive impact: flexible implementation on any OS, for many common software languages
  • Positive impact: straightforward duplication for adaptation of workflows for other projects
  • Negative impact: sometimes encourages pigeonholing of data science work into notebooks versus extending code capability into software integration
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ScreenShots